TY - GEN
T1 - A computer vision system for automatic steel surface inspection
AU - Liu, Yung Chun
AU - Hsu, Yu Lu
AU - Sun, Yung Nien
AU - Tsai, Song Jan
AU - Ho, Chiu Yi
AU - Chen, Chung Mei
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - Automatic inspection on line plays an important role in industrial quality management nowadays. This paper proposes a new computer vision system for automatic steel surface inspection. The system analyzes the images sequentially acquired from steel bar to detect different kinds of defects on the steel surface. Several image processing strategies are used to detect and outline the defects. The detected defects are then classified into different defect types by using a hierarchical neural network classifier. Some manual detection results by field experts are used to verify the correctness of the proposed detection. In defect classification, the results show that the relevance vector machine (RVM) has better accuracy than the back propagation neural network (BPN). The proposed algorithm was found capable of detecting defects on steel surface rapidly and precisely.
AB - Automatic inspection on line plays an important role in industrial quality management nowadays. This paper proposes a new computer vision system for automatic steel surface inspection. The system analyzes the images sequentially acquired from steel bar to detect different kinds of defects on the steel surface. Several image processing strategies are used to detect and outline the defects. The detected defects are then classified into different defect types by using a hierarchical neural network classifier. Some manual detection results by field experts are used to verify the correctness of the proposed detection. In defect classification, the results show that the relevance vector machine (RVM) has better accuracy than the back propagation neural network (BPN). The proposed algorithm was found capable of detecting defects on steel surface rapidly and precisely.
UR - http://www.scopus.com/inward/record.url?scp=77956043223&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77956043223&partnerID=8YFLogxK
U2 - 10.1109/ICIEA.2010.5515197
DO - 10.1109/ICIEA.2010.5515197
M3 - Conference contribution
AN - SCOPUS:77956043223
SN - 9781424450466
T3 - Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
SP - 1667
EP - 1670
BT - Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
T2 - 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
Y2 - 15 June 2010 through 17 June 2010
ER -